Liaquat Ahmad

Designing of X-bar control charts based on process capability index using repetitive sampling

A control chart, being an important tool of statistical process control, has been used for process monitoring and detection of any out-of-control process situation. In this paper, the Shewhart X ¯ chart, also known as the traditional control chart, in combination with the process capability index C p proposed by Subramani and Balamurali, is presented under the repetitive sampling scheme. The optimal design parameters of the proposed control chart are calculated. The performance of the proposed control chart is evaluated through the average run lengths (ARLs). Numerical tables have been constructed for the purpose of comparing the in-control ARL and the out-of-control ARL with the single sampling scheme. The findings of the study show that the newly suggested sampling scheme is better than the existing single sampling scheme in detection of mean shift of the process.

The design of a new repetitive sampling control chart based on process capability index

Control charts are widely used to monitor manufacturing processes for a deterioration in stability. We propose repetitive group sampling control charts based on the process capability index Cpk for monitoring process average when the quality characteristic follows a normal distribution. The performance of the repetitive Cpk control chart is reported and compared with the existing control chart in terms of the average run length. It is found that the proposed control chart is effective for quickly detecting small shifts in the process mean.

A control chart for multivariate Poisson distribution using repetitive sampling

ABSTRACT Control charts using repetitive group sampling have attracted a great deal of attention during the last few years. In the present article, we attempt to develop a control chart for the multivariate Poisson distribution using the repetitive group sampling scheme. In the proposed control chart, the monitoring statistic from the multivariate Poisson distribution has been used for the quick detection of the deteriorated process to avoid losses. The control coefficients have been estimated using the specified in-control average run lengths. The procedure of the proposed control chart has been explained by using the real-world example and a simulated data set. It has been observed that the proposed control chart is an efficient development for the quick detection of the nonrandom change in the manufacturing process.

A Control Chart for COM–Poisson Distribution Using Multiple Dependent State Sampling

In this article, an attribute control chart has been proposed for the COM–Poisson distributed non-conformities using multiple dependent states sampling based on the exponentially weighted moving average statistic. Average run lengths of the out-ofcontrol process with different shift levels of the COM–Poisson distribution have been calculated through simulation. From comparison, it has been observed that the proposed control chart is better in detecting the out-of-control process quickly as compared with the existing control chart. A simulated example has been given for the practical use of the proposed control chart. Copyright

Economic Significance of Tropical Theileriosis on a Holstein Friesian Dairy Farm in Pakistan

Abstract The dairy industry in Pakistan is booming, and investors are anxious to fund dairy farms that are using high-milk-producing (exotic) cattle breeds such as Holstein Friesians that are not native to the country. Unfortunately, the benefits of increased milk production do not provide resistance to pathogens present in regions where the exotic breeds are introduced. Therefore, the current study was conducted to evaluate the economic impact of Theileria annulata on a commercial Holstein Friesian dairy farm in the District of Ranjanpur, in the Province of Punjab, Pakistan. The economic impact of T. annulata infection was calculated for cattle with subclinical and clinical theileriosis. Losses were estimated based on milk production, morbidity, mortality, and tick control costs (organophosphate sprays). Animals were classified into groups after screening for mastitis, teat abnormality, abnormal parturition, intestinal parasites, and hemoparasites (T. annulata, Babesia spp., and Anaplasma spp.). Microscopy was done for hemoparasites and intestinal parasites. PCR was used to confirm microscopic identification of T. annulata. Animals were classified into 3 groups: group A (normal), group B (subclinical theileriosis), and group C (acute theileriosis). Hemoparasites were observed microscopically in 28.7% of cows. Theileria annulata was found in 8%, and the herd incidence (new cases) of T. annulata was 2.8%. Milk production, animal rectal temperature, and body condition scores between group A and groups B and C were significantly different (P < 0.05). But the enlargement of sub-scapular lymph node and interval of body condition score of the 3 groups were not significant (P > 0.05). The total expenditure incurred due to theileriosis was US

A mixed control chart using process capability index

74.98 per animal and 13.83% of total farm costs. Hence theileriosis caused significant economic loss of US

A control chart for COM-Poisson distribution using a modified EWMA statistic

18,743.76 (0.02 million) on this Holstein Friesian dairy.

An attribute control chart using discriminant limits for monitoring process under the Weibull distribution

ABSTRACT Control charts are considered as a compulsory tool for the monitoring and improvement of the quality of products. The commonly used attribute and the variable control charts are unsatisfactory for process monitoring. To overcome this difficulty, we proposed a monitoring scheme that is an improved technique based on the joint merits of the attribute as well as the variable control charts. The control chart coefficients have been determined for in-control and out-of-control situations for specified average run length values using simulation. The efficiency of the proposed control chart has been evaluated using average run length criteria for different values of the process settings. A practical example has been studied for implementation of the proposed technique. It has been observed that the proposed chart performs well for the mixed technique under the process capability index.

Optimal designing of an SkSP-R double sampling plan

ABSTRACT In this paper, a control chart has been developed for the Conway–Maxwell Poisson (COM-Poisson) distribution using the modified exponentially weighted moving average statistic. The proposed chart provides an efficient detection of smaller changes in the location parameter of the COM-Poisson distribution. The performance of the proposed control chart has been evaluated by the average and the standard deviation of the run length distribution for various parameters. Better detecting ability has also been compared with the existing control chart using EWMA statistic. Using simulation, we also showed the detecting ability over the traditional EWMA chart.

A EWMA control chart based on an auxiliary variable and repetitive sampling for monitoring process location

A new efficient process monitoring scheme has been developed for a process under which the quality characteristic follows the Weibull distribution. Recently control charts using discriminant limits for process monitoring for a normal distribution have been developed. But, there are many situations in which the distribution of underlying data is not normal. So, the application of such chart to a skewed distribution like the Weibull distribution may lead to erroneous conclusions. In this paper, an attribute chart using discriminant limits for the Weibull distribution has been developed. The parameters of the proposed chart have been determined by considering the in-control average run lengths. An example using the simulation data has been included for the practical use of the proposed scheme. It has been observed that the proposed chart is efficient for the quick detection of an out-of-control process. A real example from a healthcare area is also added to show the application of the proposed control chart.